给出了组合导航的状态方程和量测方程，并通过数学仿真验证了该组合导航算法的可行性。
Secondly, studies application of kalman filtering in the INS/GPS integrated navigation system. The state equation and measurement equation of integrated navigation system are given.
为了弥补现有组合导航算法的不足，提出了一种新的GPS量测数据和惯性导航系统(INS)数据的融合算法。
A new fusion algorithm of the measurements from global positioning system (GPS) and inertial navigation system (INS) is presented to compensate the weaknesses of current integrated navigation system.
利用SINS与全球定位系统（GPS）各自的速度、位置输出构造量测，设计SINS/GPS组合导航算法。
The velocity outputs and position outputs from SINS and global positioning system(GPS) were used to construct the observation, and the algorithm of SINS/GPS integrated navigation was designed.
本文提出一种自适应滤波算法，并应用于组合导航系统。
Toand vergence, an adaptive filtering technique is proposed and applied to the integrated navigation system.
仿真试验结果表明，该算法在提高组合导航系统的定位精度及可靠性和完整性方面是有效的。
The experimental results show that this algorithm is effective for the improvement of the locating accuracy, reliability and integrity of automatic vehicle integrated navigation system.
针对舰船组合导航中的有色噪声系统滤波融合问题，本文将现有的能处理白噪声的顺序滤波算法推广到有色噪声系统情形。
For colored noise system filtering fusion of vessel integrated navigation, the paper promote present sequential filtering algorithm from deal with white noise system to colored noise.
提出了一种基于神经元状态融合的组合导航系统信息融合模型，给出了神经元融合权重在线自适应学习算法。
An information fusion model of integrated navigation system based on neurons is proposed, and also an on line adaptive training algorithm of the weights of neuron is given.
基于分散滤波理论的联合滤波算法在组合导航系统中得到了广泛的应用。
The federated filtering algorithm, which is based on the decentralized filtering theory, has been widely used in integrated navigation systems.
导航算法是组合导航系统中的关键技术。
Navigation algorithm is the key technique of integrated navigation system.
研究了一种虚拟状态滤波算法与UD分解法相结合的方法，并将其应用于组合导航系统的导航参数估计过程中。
In this paper, a method of combining the virtual filtering algorithm with UD decomposition is proposed and applied to the integrated navigation system.
鉴于常规卡尔曼滤波算法组合导航系统数据融合算法中，存在易于发散的缺陷，尝试将遗传优化人工神经网络引入组合导航系统中。
As the conventional Kalman filter is liable to get divergence in integrated navigation system data fusion, an artificial neural network based on the genetic algorithms was applied in the system.
试验表明，该组合导航滤波算法实时性好，精度高，具有较好的工程应用价值。
And the result indicated that the integrated navigation filtering method has good real-time performance and high accuracy, which shows better value of engineering application.
针对当前自适应组合导航系统算法的研究趋势，总结了卡尔曼滤波技术的缺陷和利用智能融合技术提高滤波器性能的设计思想。
The adaptive Kalman filtering (AKF) based on intelligent information fusion algorithm has currently became an effective approach to enhance the integrated navigation system's robustness and accuracy.
研究了应用线性网络对组合导航多传感器信息进行融合的方法，在此基础上提出了一种神经网络组合导航容错算法。
In this paper, a method of multi-sensor data fusion using neural network in integrated navigation system is given, and then a fault-tolerant algorithm is proposed.
采用了卡尔曼滤波为核心算法的数据融合，来提高组合导航系统的定位精度和可靠性。
This system takes the Kalman filter as core algorithm to fuse data so that the positioning accuracy and system reliability can be improved.
本文提出一种分级式分敞信息滤波算法，并通过具体实例研究了它在组合导航系统中的应用。
An algorithm of decentralized information filtering with hierarchical network structures is discussed for the design of integrated navigation system.
提出了一种北斗卫星定位系统和惯性导航系统的组合导航无源定位算法。
A passive location algorithm for the integrated navigation system of Beidou and inertial navigation system (INS) was put forward in this paper.
然后针对MIMU/GPS组合导航的数据时间同步问题，提出了一种新的GPS时间延迟补偿算法。
To study the data synchronization problem of MIMU/GPS integrated navigation systems, a new data synchronization method for GPS measurement data delay is proposed.
针对车载组合导航信息融合的高精度、高可靠性等要求，提出了一种组合导航的自适应集中滤波算法。
Through combining dead reckoning, GPS positioning information and Map-Matching algorithm, this paper represents an algorithm to correct sensors parameters in In-Vehicle Navigation System.
针对车载组合导航信息融合的高精度、高可靠性等要求，提出了一种组合导航的自适应集中滤波算法。
Through combining dead reckoning, GPS positioning information and Map-Matching algorithm, this paper represents an algorithm to correct sensors parameters in In-Vehicle Navigation System.
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